Source code for immuneML.app.ImmuneMLApp

import argparse
import datetime
import logging
import os
import shutil
import warnings
from pathlib import Path

from immuneML.caching.CacheType import CacheType
from immuneML.dsl.ImmuneMLParser import ImmuneMLParser
from immuneML.dsl.semantic_model.SemanticModel import SemanticModel
from immuneML.dsl.symbol_table.SymbolType import SymbolType
from immuneML.environment.Constants import Constants
from immuneML.environment.EnvironmentSettings import EnvironmentSettings
from immuneML.util.PathBuilder import PathBuilder
from immuneML.util.ReflectionHandler import ReflectionHandler


[docs]class ImmuneMLApp: def __init__(self, specification_path: Path, result_path: Path): self._specification_path = Path(specification_path) self._result_path = Path(os.path.relpath(result_path)) PathBuilder.build(self._result_path) self._cache_path = self._result_path / "cache"
[docs] def set_cache(self): os.environ[Constants.CACHE_TYPE] = CacheType.PRODUCTION.value EnvironmentSettings.set_cache_path(self._cache_path)
[docs] def clear_cache(self): shutil.rmtree(self._cache_path, ignore_errors=True) EnvironmentSettings.reset_cache_path() del os.environ[Constants.CACHE_TYPE]
[docs] def run(self): self.set_cache() print(f"{datetime.datetime.now()}: ImmuneML: parsing the specification...\n", flush=True) symbol_table, self._specification_path = ImmuneMLParser.parse_yaml_file(self._specification_path, self._result_path) print(f"{datetime.datetime.now()}: ImmuneML: starting the analysis...\n", flush=True) instructions = symbol_table.get_by_type(SymbolType.INSTRUCTION) output = symbol_table.get("output") model = SemanticModel([instruction.item for instruction in instructions], self._result_path, output) result = model.run() self.clear_cache() print(f"{datetime.datetime.now()}: ImmuneML: finished analysis.\n", flush=True) return result
[docs]def run_immuneML(namespace: argparse.Namespace): if os.path.isdir(namespace.result_path) and len(os.listdir(namespace.result_path)) != 0: raise ValueError(f"Directory {namespace.result_path} already exists. Please specify a new output directory for the analysis.") PathBuilder.build(namespace.result_path) logging.basicConfig(filename=Path(namespace.result_path) / "log.txt", level=logging.INFO, format='%(asctime)s %(levelname)s: %(message)s') warnings.showwarning = lambda message, category, filename, lineno, file=None, line=None: logging.warning(message) if namespace.tool is None: app = ImmuneMLApp(namespace.specification_path, namespace.result_path) else: app_cls = ReflectionHandler.get_class_by_name(namespace.tool, "api/") app = app_cls(**vars(namespace)) app.run()
[docs]def main(): parser = argparse.ArgumentParser(description="immuneML command line tool") parser.add_argument("specification_path", help="Path to specification YAML file. Always used to define the analysis.") parser.add_argument("result_path", help="Output directory path.") parser.add_argument("--tool", help="Name of the tool which calls immuneML. This name will be used to invoke appropriate API call, " "which will then do additional work in tool-dependent way before running standard immuneML.") namespace = parser.parse_args() namespace.specification_path = Path(namespace.specification_path) namespace.result_path = Path(namespace.result_path) run_immuneML(namespace)
if __name__ == "__main__": main()